Digital Disruption and the Future of Leadership: An Interview With Rick Haythornthwaite, Chairman of Centrica and MasterCard

© 2016, © The Author(s) 2016. Unprecedented changes in the nature and prevalence of digital technology have significant implications for leadership theory, practice, and development that, as yet, remain largely unexplored in mainstream academic literature. This article features an interview with Rick Haythornthwaite, Chairman of global businesses including Centrica and MasterCard, where he reflects on the ways in which digital disruption is impacting upon the nature of leadership and strategic practice. It is accompanied by a commentary that highlights the importance of factors such as context, trust, ethics, and purpose in a fast moving corporate world

Linear-scaling DFT+U with full local orbital optimization

We present an approach to the DFT+U method (Density Functional Theory + Hubbard model) within which the computational effort for calculation of ground state energies and forces scales linearly with system size. We employ a formulation of the Hubbard model using nonorthogonal projector functions to define the localized subspaces, and apply it to a local-orbital DFT method including in situ orbital optimization. The resulting approach thus combines linear-scaling and systematic variational convergence. We demonstrate the scaling of the method by applying it to nickel oxide nano-clusters with sizes exceeding 7,000 atoms.Comment: 10 pages, 4 figures. This version (v3) matches that accepted for Physical Review B on 30th January 201

Leading to Achieve Social Change: An Interview with Ruth Hunt, Former Chief Executive Officer of Stonewall

In this interview, Ruth Hunt, former CEO of the lesbian, gay, bi, and trans equality charity Stonewall and now crossbench peer at the House of Lords, discusses her approach to leadership for social change. She considers the changing context of LGBT rights, her motives for joining the organization, experiences and learning from leading change on this agenda, and the challenges of addressing power, privilege, and embedded cultural norms in order to create a truly inclusive workplace. Key themes include managing the tensions between an assimilation and liberation approach to social change, promoting intersectionality and positive action to enhance inclusion, the challenges and opportunities of sharing power and the skills of facilitation, boundary-spanning and working relationally that constitute the everyday practice of leadership in complex and contested landscapes. A commentary is provided that highlights links to and implications for leadership, management and organization scholarship, education and practice

From feeding-back to feeding-forward: managerial feedback as a trigger of change in SMEs

© 2018, Emerald Publishing Limited. Purpose: The purpose of this paper is to explore and theorize the process of managerial feedback in relation to change in small and medium enterprises (SMEs). Design/methodology/approach: This research embraces a qualitative methodology in the context of manufacturing SMEs. Drawing on 30 in-depth interviews, and observations conducted with various managers in six SMEs operating in three countries, it is argued that managers benefit more by using daily, ongoing, feedback as a trigger of change in their organizations. Findings: The findings suggest that there is an overall view that managers appear to be reluctant to change existing processes using formalized feedback mechanisms, which runs counter-intuitive to the literature. In contrast, informal methods of feedback work better in enhancing organizational change. Moreover, another two features of feedback enhance this process, namely, benefits oriented and confidence oriented. As such, this study contributes to existing knowledge and practice by proposing a three-fold form of feedback through which managers expand their perspectives of feedback from feeding-back to feeding-forward thereby enhancing the opportunities of triggering change. Research limitations/implications: Feedback should merely be considered as a dynamic and socially constructed managerial practice. A practice where actors not only exchange information and share knowledge, but also act, react and interact with each other as they constantly rethinking the change process. The proposed aspect of feedback emphasizes knowledge therapeutically and in combination with the dialogical discourse (practical illustration) that increases the odds for capturing change as a natural, rather than exceptional. Practical implications: Practitioners, as such, may wish to consider the terminology used when it comes to studying change and its implementation in a crisis context. Using deformalized managerial feedback mechanisms to tackle a formal phenomenon like “change” could help avoid employees perceiving a negative connotation, causing resistance or confusion and feeling threatened. Therefore, the authors suggest that practitioners, during development initiatives on modernizing or altering organizational processes, consider replacing the term “change” as a formal concept. Originality/value: It is an investigation from an exploratory perspective in studying and understanding the causes, factors and modalities that trigger managerial feedback toward organizational change in manufacturing SMEs

Vanadium dioxide : A Peierls-Mott insulator stable against disorder

Vanadium dioxide undergoes a first order metal-insulator transition at 340 K. In this work, we develop and carry out state of the art linear scaling DFT calculations refined with non-local dynamical mean-field theory. We identify a complex mechanism, a Peierls-assisted orbital selection Mott instability, which is responsible for the insulating M$_1$ phase, and furthermore survives a moderate degree of disorder.Comment: 5 pages, 4 figures. Supplementary material 8 pages, 4 figures. This version (v2) matches that accepted for Physical Review Letters on 16th May 201

Towards conceptualizing reverse service supply chains

Purpose – Recognizing the heterogeneity of services, this paper aims to clarify the characteristics of forward and the corresponding reverse supply chains of different services. Design/methodology/approach – The paper develops a two-dimensional typology matrix, representing four main clusters of services according to the degree of input standardization and the degree of output tangibility. Based on this matrix, this paper develops a typology and parsimonious conceptual models illustrating the characteristics of forward and the corresponding reverse supply chains of each cluster of services. Findings – The four main clusters of service supply chains have different characteristics. This provides the basis for the identification, presentation and explanation of the different characteristics of their corresponding reverse service supply chains. Research limitations/implications – The findings of this research can help future researchers to analyse, map and model forward and reverse service supply chains, and to identify potential research gaps in the area. Practical/implications – The findings of the research can help managers of service firms to gain better visibility of their forward and reverse supply chains, and refine their business models to help extend their reverse/closed-loop activities. Furthermore, the findings can help managers to better optimize their service operations to reduce service gaps and potentially secure new value-adding opportunities. Originality/value – This paper is the first, to the authors ' knowledge, to conceptualize the basic structure of the forward and reverse service supply chains while dealing with the high level of heterogeneity of services

Disease-specific variant pathogenicity prediction significantly improves variant interpretation in inherited cardiac conditions

Funder: Science and Technology Development Fund; doi: https://doi.org/10.13039/Funder: Al-Alfi FoundationFunder: Magdi Yacoub Heart FoundationFunder: Rosetrees and Stoneygate Imperial College Research FellowshipFunder: National Health and Medical Research Council (Australia)Abstract: Purpose: Accurate discrimination of benign and pathogenic rare variation remains a priority for clinical genome interpretation. State-of-the-art machine learning variant prioritization tools are imprecise and ignore important parameters defining gene–disease relationships, e.g., distinct consequences of gain-of-function versus loss-of-function variants. We hypothesized that incorporating disease-specific information would improve tool performance. Methods: We developed a disease-specific variant classifier, CardioBoost, that estimates the probability of pathogenicity for rare missense variants in inherited cardiomyopathies and arrhythmias. We assessed CardioBoost’s ability to discriminate known pathogenic from benign variants, prioritize disease-associated variants, and stratify patient outcomes. Results: CardioBoost has high global discrimination accuracy (precision recall area under the curve [AUC] 0.91 for cardiomyopathies; 0.96 for arrhythmias), outperforming existing tools (4–24% improvement). CardioBoost obtains excellent accuracy (cardiomyopathies 90.2%; arrhythmias 91.9%) for variants classified with >90% confidence, and increases the proportion of variants classified with high confidence more than twofold compared with existing tools. Variants classified as disease-causing are associated with both disease status and clinical severity, including a 21% increased risk (95% confidence interval [CI] 11–29%) of severe adverse outcomes by age 60 in patients with hypertrophic cardiomyopathy. Conclusions: A disease-specific variant classifier outperforms state-of-the-art genome-wide tools for rare missense variants in inherited cardiac conditions (https://www.cardiodb.org/cardioboost/), highlighting broad opportunities for improved pathogenicity prediction through disease specificity

Disease-specific variant pathogenicity prediction significantly improves variant interpretation in inherited cardiac conditions

Funder: Science and Technology Development Fund; doi: https://doi.org/10.13039/Funder: Al-Alfi FoundationFunder: Magdi Yacoub Heart FoundationFunder: Rosetrees and Stoneygate Imperial College Research FellowshipFunder: National Health and Medical Research Council (Australia)Abstract: Purpose: Accurate discrimination of benign and pathogenic rare variation remains a priority for clinical genome interpretation. State-of-the-art machine learning variant prioritization tools are imprecise and ignore important parameters defining gene–disease relationships, e.g., distinct consequences of gain-of-function versus loss-of-function variants. We hypothesized that incorporating disease-specific information would improve tool performance. Methods: We developed a disease-specific variant classifier, CardioBoost, that estimates the probability of pathogenicity for rare missense variants in inherited cardiomyopathies and arrhythmias. We assessed CardioBoost’s ability to discriminate known pathogenic from benign variants, prioritize disease-associated variants, and stratify patient outcomes. Results: CardioBoost has high global discrimination accuracy (precision recall area under the curve [AUC] 0.91 for cardiomyopathies; 0.96 for arrhythmias), outperforming existing tools (4–24% improvement). CardioBoost obtains excellent accuracy (cardiomyopathies 90.2%; arrhythmias 91.9%) for variants classified with >90% confidence, and increases the proportion of variants classified with high confidence more than twofold compared with existing tools. Variants classified as disease-causing are associated with both disease status and clinical severity, including a 21% increased risk (95% confidence interval [CI] 11–29%) of severe adverse outcomes by age 60 in patients with hypertrophic cardiomyopathy. Conclusions: A disease-specific variant classifier outperforms state-of-the-art genome-wide tools for rare missense variants in inherited cardiac conditions (https://www.cardiodb.org/cardioboost/), highlighting broad opportunities for improved pathogenicity prediction through disease specificity